Here is a research paper that discusses using adiabatic quantum computation using liquid state nuclear magnetic resonance quantum computers for pattern recognition.
Dwave systems has used their quantum computer for image matching.
A novel quantum pattern recognition scheme is presented, which combines the idea of a
classic Hopfield neural network [shown to the left] with quantum adiabatic computation. Both the input and the memorized patterns are represented by means of the problem Hamiltonian. In contrast to classic neural networks, the algorithm can simultaneously return multiple recognized patterns. The approach also promises extension of classic memory capacity. A proof of principle for the algorithm for two qubits is provided using a liquid state NMR quantum computer.
In contrast to classic neural networks, a quantum neural register can represent a superposition of recognized patterns. Quantum superposition allows each of these patterns to be identified which is not the case for linearly combined mixture states in classic neural networks.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.